Artificial intelligence has been defined as computer software that is highly trained to perform a task or perform a series of tasks with the use of algorithms and artificial intelligence. As with all software, the quality of the artificial intelligence is determined by its programming language. For artificial intelligence to be complete it must also be able to interact naturally with humans in situations where it is not fully understood. The definition of artificial intelligence can sometimes be difficult for programmers to understand, but it can be explained in simple terms:
Artificial intelligence is a general term that covers many applications in diverse domains such as manufacturing, decision-making, online games, digital devices, finance, marketing etc. Machine learning refers to applications in which computer software is trained to anticipate user input and behave accordingly. In other words, artificial intelligence is about achieving a state of the art performance by a machine while human intelligence covers issues such as problem solving, speech recognition etc. Deep learning refers to the combination of these two areas and is rapidly emerging as the most important area of artificial intelligence today.
Programming language is a necessary part of artificial intelligence. Today, more than a third of all scientific papers are produced using languages such as C++, Java, MATLAB, R, Python, SQL, etc., so that the future of computer science is well on its way. However, even though these programming languages are extremely powerful, they are limited by the difficulty of designing and evaluating artificial intelligence systems. In order to design AIs, the programmers must be well versed in the programming languages they will be using. The programs that form the basis of artificial intelligence must also be updated regularly. As new machine learning tools and algorithms emerge, these tools and algorithms will become even more complicated and difficult to program.
A natural language processing system can be defined as a set of rules specifying how computers, humans or other artificial intelligence machines will communicate. These rules can be written in a number of different places such as English, Spanish, Chinese, French, German etc. Each different language has its own idiosyncrasies that need to be taken into account when writing programs for these devices. This is one of the major limiting factors of artificial intelligence.
Natural Language Processing does not provide a direct path to artificial intelligence. Instead it aims to provide machines with a set of rules specifying how a particular machine will reason. For instance, if we were to program a machine to play a chess game we would need to specify a number of chess pieces to be allowed and their position on the chessboard, the pieces’ color and the pieces’ value so that the machine can reason correctly. Similarly, to program AI machines to reason properly a user would need to teach these machines how to reason.
Deep learning involves embedding these reasoning trees into artificial intelligence systems. Once these trees are fully embedded, the machines can reason rationally. Some argue that this can only be achieved by creating very sophisticated algorithms that are optimized for certain types of inputs and gradients or levels of difficulty. The argument that Deep Learning gives rise to is that because an algorithm is used many times a day by Deep Learners, it forms a pattern of algorithms which can be learned easily and can be applied to many different applications. It also provides a readymade framework for developers who are able to extend the functionality of existing machines.
However, a different group of researchers argue that while Deep Learning does have some advantages over the status of artificial intelligence, its future lies in various directions. They claim that we cannot have intelligent agents without human operators, therefore we cannot have artificially intelligent agents without human operators, therefore and so on. Another group of researchers claim that all forms of artificially intelligent machines will be limited by their programmers’ ability to reason correctly and efficiently. The conclusion which can be drawn from this is that while human beings are capable of reasoning efficiently and clearly, we still have a long way to go before machines can do the same.
Both sides of the argument put forward compelling points. What is important is that one has to take into consideration that whatever may be the nature of AI machines, there is still a way forward, a road map towards achieving Artificial Intelligences, whether they are operated by humans or by AI machines. Hence, whether one thinks of Alpha, Beta or Gamma AI, the goal remains the same, and that is to achieve Artificial Intelligence. In the next part of this series, we shall look at the current status of such Artificial Intelligent Systems, what they are capable of and how far they are away from human thinking machines.